Recap I

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# Recap I
### The R Bootcamp <a href='https://therbootcamp.github.io'>www.therbootcamp.com</a> <a href='https://twitter.com/therbootcamp'>@therbootcamp</a>
### July 2018

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<a href="https://therbootcamp.github.io/">Basel, July 2018</a>
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<a href="https://therbootcamp.github.io/">www.therbootcamp.com</a>
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# Essentials: The 24 Lessons of the R Bootcamp

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1. Everything is an object
2. Use `<-` to create/change objects
3. Name objects using `_`
4. Objects have classes
5. Everything happens through functions
6. Functions have (default) arguments
7. Functions expect certain object classes
8. View help files using `?`
9. Study errors and warnings
10. Data is stored in data frames
11. Select variables (vectors) using `$`
12. Use RStudio and projects
13. Use editor and shortcuts
14. First load packages and data
15. Use auto-complete
16. Comment and format for readability
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# 3 Object types for data

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R has 3 main data objects...

<high>`list`</high> - R's multi-purpose container
- Can carry any data, incl. lists
- Often used for function outputs

<high>`data_frame`</high> - R's spreadsheet
- Specific type of `list`
- Typical data format
- For multi-variable data sets

<high>`vectors`</high> - R's data container
- Actually carries the data
- Contain data of 1 of many types

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<img src="https://raw.githubusercontent.com/therbootcamp/therbootcamp.github.io/master/_sessions/_image/main_objects.png"></img>
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# Functions

Functions have 3 elements:

1 - <high>Name</high>: Used to refer to the function and call (execute) it.

2 - <high>Arguments</high>: Used to provide (data) inputs and to control what the function does. Arguments with default values (e.g., `use = "everything"`) need not be specified. Arguments without default values (e.g., `x`) need be specified. <high>Inputs must have the appropriate class!</high>

3 - <high>Body</high>: The code that uses the inputs (arguments) to produce the desired output. The code of the functions body is based <high>copies of the inputs</high>, which are named according to the arguments names.

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 <img src="https://raw.githubusercontent.com/therbootcamp/therbootcamp.github.io/master/_sessions/_image/function.png"></img>
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# Documentation

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R documentation (<high>help files</high> and <high>vignettes</high>) will become very to use once you are familiar with the basic R vocabulary.

Pay attention to...

<high>Usage</high> - shows how to use function, its arguments and their defaults. <high>Arguments</high> - describes arguments, and their `class`. <high>Value</high> - describes what the function returns. <high>Examples</high> - provide working R code.

```r
# To access help files
?name_of_function

# search help files
??name_of_function
```

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```r
?cor
```
<img src="https://raw.githubusercontent.com/therbootcamp/therbootcamp.github.io/master/_sessions/_image/help_cor.png" width="500">
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# The almighty `tidyverse`

Among its many packages, R newly contains a collection of high-performance, user-friendly packages (libraries) known as the [tidyverse](https://www.tidyverse.org/). The tidyverse includes:
1. `ggplot2` -- creating graphics.
2. `dplyr` -- data manipulation.
3. `tidyr` -- tidying data.
4. `readr` -- read wild data.
5. `purrr` -- functional programming.
6. `tibble` -- modern data frame.

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<hfont><high>Questions?</high></hfont> 
 <a href = "https://therbootcamp.github.io/BaselRBootcamp_2018July/">Link to schedule</a>

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